Such a method for example finds a technical application for echo suppression during intercom talking, for the transmission of analog or digital signals via long lines or via 2-wire/4-wire converters, and in mobile radio networks with both the DECT standard and the GSM standard.
The basic idea of echo compensation comprises the simulation of a real system, for example the loudspeaker-room-microphone system during intercom talking, see R. Wehrmann et al.: Signal processing method for improving voice communication via intercom stations, The Telecommunications Engineer, Science and Life Publishers Georg Heidecker GmbH, Erlangen, 48th. year, October 1994, pages 27-29. The signal that arrives at the receiver then passes through the real and the simulated system. The echo signal formed by the simulated system is subtracted from the real echo signal, so that the echo is compensated except for a residual error.
Digital filters, particularly FIR (Finite Impulse Response) filters proved to be especially suitable.
According to FIG. 1, an FIR filter 1 essentially comprises a number n of memories 11, . . . , 1n switched in a chain connection, which respectively store a sampled value x(k-.tau.) of the input signal, and a number of multipliers 21, . . . , 2n whereby the output signal of each memory 11, . . . , 1n is multiplicatively weighted with a set of filter coefficients ci where 1.ltoreq.i.ltoreq.n, and a summator 3 which adds all the weighted signals to an output signal 4. The filter coefficients ci must be adjusted so that the FIR filter 1 simulates a signal that corresponds to each real echo, which is then subtracted from the disturbed signal to eliminate the echoes. Generally the echoes can only be simulated by the FIR filter 1 with limited accuracy by expending a practical effort, so that the echo cannot be entirely eliminated from the disturbed signal and thus no complete echo compensation can be achieved but rather only an echo attenuation.
In this case the correct adjustment of the filter coefficients ci exerts a significant influence on the achievable echo attenuation. It can be attained once with accurate measuring means. But such a process has the disadvantage that a new measurement must be performed with each change of the real echo, and a new adjustment of the filter coefficients ci is required.
It is known to carry out a continuous measurement with an automatic adjustment of the filter coefficients ci in accordance with the NLMS (Normalized Least Mean Square) algorithm, see R. Wehrmann et al.: Signal processing method for improving voice communication via intercom stations, The Telecommunications Engineer, Science and Life Publishers Georg Heidecker GmbH, Erlangen, 48th. year, October 1994, pages 8-10. The filter coefficients ci(k) at the time k are calculated from those at the time (k-1) in accordance with (see equation 1), ##EQU1## where: ci(k)=i-th filter coefficients at time k
.alpha.=step size 0&lt;.alpha..ltoreq.2 PA0 y(k)=sampled value of the microphone signal with attenuated echo at time k PA0 .tau.=the smallest delay after an excitation until an echo occurs; corresponds to the shortest signal transfer time from loudspeaker to microphone PA0 n=length of the filter PA0 x(k-.tau.-i)=sampled value of the loudspeaker signal PA0 .SIGMA.x(.)=signal energy in the filter.
The filter coefficients c can be adjusted quickly and with sufficient accuracy by the NLMS algorithm if no other disturbance signals are present except for the echoes. The adjustment speed is essentially determined by the step size .alpha.. If the step size .alpha. is small, the adjustment speed is small; it increases as the step size .alpha. increases and reaches its largest value when .alpha.=2. Good convergence properties are attained with the NLMS algorithm if the echoes have a uniform broad-banded power density spectrum.
With unsuitable excitation, for example by sinusoidal signals and in the presence of disturbance signals, for example when the local speaker talks, the filter coefficients ci are misadjusted by the NLMS algorithm. The larger the step size .alpha. is, the faster this takes place. To prevent such a misadjustment of the filter coefficients ci it is known to control the magnitude of the step size .alpha. as a function of the current signal situation in order to be able to use a signal situation that is suitable for the NLMS algorithm for determining the filter coefficients ci, see DE 44 30 189.
Still, signal situations which lead to misadjustments of the filter coefficients ci occur despite the adaptive control of the step size .alpha.. A signal situation which is particularly unfavorable for the NLMS algorithm occurs if disturbance signals caused by external disturbance sources take place in addition to the echoes at the output of the microphone, signal ms(t) in FIG. 1. Such disturbance signals can be produced for example by an active local speaker, or by background noises, or by nonlinear effects in A/D (analog-to-digital) converters, or by non-harmonic resonances of loudspeakers and their cabinets. For the short term these disturbance signals can change the adjustment of the filter coefficients ci in a way so that the FIR filter does not compensate for existing echoes and even causes additional echoes in unfavorable cases, thereby deteriorating the entire situation. Even a good average echo attenuation, for example 30 dB does not exclude phases wherein the FIR filter clearly causes additional disturbances, so that a natural voice transmission is no longer provided and in certain applications the intercom stations are entirely omitted, for example during conference operations.